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  2. Numerical methods for ordinary differential equations

    en.wikipedia.org/wiki/Numerical_methods_for...

    It costs more time to solve this equation than explicit methods; this cost must be taken into consideration when one selects the method to use. The advantage of implicit methods such as ( 6 ) is that they are usually more stable for solving a stiff equation , meaning that a larger step size h can be used.

  3. Initial value problem - Wikipedia

    en.wikipedia.org/wiki/Initial_value_problem

    The Banach fixed point theorem is then invoked to show that there exists a unique fixed point, which is the solution of the initial value problem. An older proof of the Picard–Lindelöf theorem constructs a sequence of functions which converge to the solution of the integral equation, and thus, the solution of the initial value problem.

  4. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    The scheme is always numerically stable and convergent but usually more numerically intensive than the explicit method as it requires solving a system of numerical equations on each time step. The errors are linear over the time step and quadratic over the space step: Δ u = O ( k ) + O ( h 2 ) . {\displaystyle \Delta u=O(k)+O(h^{2}).}

  5. Symbolab - Wikipedia

    en.wikipedia.org/wiki/Symbolab

    Later, the ability to show all of the steps explaining the calculation were added. [6] The company's emphasis gradually drifted towards focusing on providing step-by-step solutions for mathematical problems at the secondary and post-secondary levels. Symbolab relies on machine learning algorithms for both the search and solution aspects of the ...

  6. Backward differentiation formula - Wikipedia

    en.wikipedia.org/wiki/Backward_differentiation...

    The backward differentiation formula (BDF) is a family of implicit methods for the numerical integration of ordinary differential equations.They are linear multistep methods that, for a given function and time, approximate the derivative of that function using information from already computed time points, thereby increasing the accuracy of the approximation.

  7. Adaptive step size - Wikipedia

    en.wikipedia.org/wiki/Adaptive_step_size

    In mathematics and numerical analysis, an adaptive step size is used in some methods for the numerical solution of ordinary differential equations (including the special case of numerical integration) in order to control the errors of the method and to ensure stability properties such as A-stability. Using an adaptive stepsize is of particular ...

  8. Leapfrog integration - Wikipedia

    en.wikipedia.org/wiki/Leapfrog_integration

    where is position at step , + / is the velocity, or first derivative of , at step + /, = is the acceleration, or second derivative of , at step , and is the size of each time step. These equations can be expressed in a form that gives velocity at integer steps as well: [ 2 ]

  9. Split-step method - Wikipedia

    en.wikipedia.org/wiki/Split-step_method

    In numerical analysis, the split-step (Fourier) method is a pseudo-spectral numerical method used to solve nonlinear partial differential equations like the nonlinear Schrödinger equation. The name arises for two reasons.

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